Drought Risk Management for Malawi Joanna Syroka CRMG, Agriculture & Rural Development World Bank Regional Workshop, Querétaro 9 October 2008

Malawi Background Low economic growth, with significant volatility Economy is highly vulnerable to adverse weather shocks Agriculture about 40 percent of GDP, largely smallholder rain-fed maize production

Impact of Weather Shocks Direct and indirect economic impact of weather shocks: –Direct impact on agricultural production and GDP –Indirect impact on government finances and BoP Fiscal impact due to unanticipated need for emergency interventions (resulting in increased domestic borrowing) Increased pressure on the current account due to need for exceptional food imports Further, long-term impact of the volatility is substantial, as economic uncertainty hampers investments and economic growth (World Bank CEM, 2004) Clear Malawi needs to plan for contingencies ex ante.

Malawi Context Malawi’s maize marketing policy is dominated by concerns about food insecurity Erratic Rainfall, Recurrent Drought Thin MarketsProduction Uncertainty Maize Supply/Price Volatility Food Shortages Government Responses* * 2005 Drought Response Cost: > $200 million for Government

Integrated Risk Management Problems Recurring drought Maize price supply & price volatility Thin markets & very low levels of private sector trade, finance, and storage Market Solutions Weather risk management Contingent import/export arrangements based on option contracts Warehouse receipts-based lending Government's Agricultural Development Program (ADP) focuses on strengthening maize markets in Malawi to respond to production shocks –Market-based risk management instruments can help

Weather Risk Management What is it? –Financial protection against adverse weather conditions that result in volume volatility –Contracts can be structured as insurance or derivatives –Based on the performance of a specified weather index –Payouts are made if the index crosses a specified threshold at the end of the contract period Malawi Context: –GoM is concerned about the impact of rainfall on maize production –Can provide payouts in the event of contractually specified shortfalls in rainfall during growing season –Essentially “budget insurance” for GoM –Timely access to cash in times of crisis, reducing reliance on international appeals

The Weather Market First weather derivative transaction in U.S –Deregulation of the energy industry Market has rapidly grown, well over $100b transacted to date (PWC Survey 2008) –Non-energy applications –New participants –Global development –Broader product offering Key Players: –(Re)insurers –Banks –Hedge Funds Market wants to diversify and grow their portfolios, wants new risks

Prerequisites for a Program in Malawi An index that captures national drought risk in Malawi faithfully –Government’s Maize Yield Assessment Model –Rainfall-based FAO model used since 1992 High quality historical weather data and reliable real-time communication –Malawi Met Office data excellent: 23 stations with over 40 years, few gaps –Can provide real-time data required by market $200k invested by DFID Jan 2008 to support a pilot transaction Premium: –DFID want to support initial premium cost in piloting phase starting 2008 –EU and USAID interested for 2009+

Limitations of Approach Only covers national severe drought, not localized events Only covers risks that can be indexed –Does not cover production losses due to input supply, area planted variations, pests, floods etc. Basis Risk: The potential mismatch between actual losses and payouts, can be managed by: –More secure stations –Better crop modelling and index specification –A comprehensive approach to minimize undue pressure on one instrument to manage production risk –World Bank ADP Support Project contains funds to support these investments

Malawi Maize Index vs National Production Correlation 80%

“Put Option” Payout Structure Payout per Unit Index Maximum Payout Long-Term AverageTrigger Level

Term-Sheet Example Transaction Type:Put Option Option Buyer:Government of Malawi Calculation Period:1 st November th April 2009 (inclusive) Locations:23 Reference Weather Stations Weather Variable Measured at Locations:Daily Precipitation Measurement Unit: mm Commodity Index, I:Malawi Maize Index Index Strike Level, T:95.00 Index Units Payout per Unit Index, N:$USD 500,000 per Unit Index below Strike T Max. Transaction Payment Amount, M:$USD 20,000,000 Settlement Calculation:I)If the Index I is greater than the Strike T no payment is made. II)If the Index I is less than or equal to the Strike T the Buyer receives a payout X from the Seller according to the following Settlement Calculation: X = min( max(T - I, 0)*N, M ) Premium:E.g. $USD 3,000,000

Historical Payouts Example 95% Strike, $500k per % Payout Value of Contract to Market = Average Payout + Risk Margin Value of Contract to Government = Average Payout + Value of Timely, Reliable Funds

Leveraging a Payout Example: 2005 Government purchased between 200, ,000 MT maize in October/November 2005 on the South African spot market. Had the Government been able to able to purchase the maize in June they could have saved approximately $110 per MT, i.e. between $ million. In September 2005, Government piloted the use of a SAFEX call option on 60,000 MT of maize –This cost the Government $1.7 million in premium –It saved the Government $80 per MT, i.e. $4.8 million Had the Government had a payout from weather insurance in June 2005 they could have bought a call option for 60,000 MT of maize –A $2 million payout would have saved $110 per MT on 60,000 MT of maize, i.e. a total saving of $6.6 million This is equal to a leveraging effect of x 4 –Significantly smaller than the “risk margin” charged by insurers Value of contract to Government > premium charged by insurer

E.g. Future Scenario for Drought Response Purchase insurance Measure & monitor daily rainfall throughout season JulOct- April Payout for drought May Purchase of SAFEX call option June- July Encourage commercial imports Aug- Oct Nov Imports through Option Dec- Jan Exercise Option

Operational Arrangements Approved by World Bank Executive Board, June 2008 Market Counterparty World Bank Government of Malawi (MoF) Data Provider Premium Payout Premium Payout Data Verification Data Verification Transaction Flow  The Government of Malawi (GoM) will enter into a weather derivative agreement with the World Bank. In exchange for a premium, Malawi will be covered against drought-related financial risk  The GoM will receive a payout from the World Bank if the index hits a pre-determined trigger. The trigger is selected by the GoM, based on coverage and cost considerations  The World Bank will enter into a mirroring agreement with a market counterpart that will “compensate” the World Bank in case the trigger is hit  Charges to the GoM will be determined on a pure cost recovery basis (premium charged to the Bank by the market counterpart and administrative cost)  Intermediation service is available to all IBRD and IDA clients (given certain pre-requisites) – first time an IDA country can access a derivative product from World Bank Treasury

World Bank Intermediation: Value Added  Reduces start-up costs for private sector market players in Malawi  Facilitates competition by organizing bidding process among market counterparts Attracting Market Players  Market participants are concerned about possible manipulation of weather data as the data provider (Met-Office) is a Government agency. The World Bank involvement eases these concerns Mitigating Moral Hazard Concerns  As risk and start-up cost is reduced for the counterparts, and the Bank facilitates competition, the pricing might benefit from World Bank intermediation Pricing  Building capacity to facilitate future direct transactions between the Government and market counterparts  Legal  Transaction structuring. E.g. choice of the coverage level  Bidding process, execution, valuation, accounting Building Capacity

Proposal for 2008/9 and Beyond For 2008/9: –Pilot a transaction through competitive market process (with World Bank Treasury assistance) –Critical for price and process discovery –Link potential payout to maize or SAFEX call option purchases 2009 onwards (funded as part of World Bank 5-yr ADP Support Project): –Further investment in Met Office network Improve index by better regional coverage Reduce risk-transfer costs by increasing market confidence in settlement data –Improve Government’s Maize Yield Assessment Model Include impact of excess rainfall –Link with national early warning system to strengthen drought preparedness and planning Value of contingency funds is in effective planning –Understand the role of weather insurance in Government’s suite of risk management tools Designed to work in tandem with other tools TA and capacity building for Government Establish budget line for premiums